FIT HUB is a venture-backed technology driven health and wellness startup based in Jakarta, Indonesia. Founded in 2020, FIT HUB’s mission is to democratize access to Health and Wellness for all Indonesians. We believe that everyone should have access to improving their health and wellness, so we’ve built FIT HUB from the ground up to make exercising friendly, affordable, and fun for new gym-goers and fitness-enthusiasts alike.
The Opportunity:
As a Data Engineer, you will be part of our growing Data Team and play a key role in building and operating reliable data foundations that power business reporting, product analytics, and advanced analytics use cases. This role has strong ownership in areas such as curated datasets for sales, user activities (class check-in, personal trainer conduct), and membership analytics, feature pipelines to support scoring and analytics, privacy controls (masking and access management), reliability (data quality and alerting), and platform cost efficiency. You will work cross-functionally with Product, Tech, Data, Commercial, Finance, and the CEO Office to deliver trusted and scalable data products.
What You Will Do:
- Build and maintain production-grade data pipelines (batch and event-based) that power core business reporting and decision-making (sales funnels, membership and renewal metrics, monthly performance reporting).
- Develop curated datasets and data models (silver/gold/platinum thinking) to improve metric consistency, usability, and performance for dashboards and analytics.
- Support migration and modernization work: migrate legacy reports/queries to optimized datasets and improve maintainability of analytics assets.
- Enable machine learning delivery by building and maintaining feature pipelines and feature store patterns to support offline and online use cases (e.g., lead scoring).
- Improve reliability and observability: monitor pipeline health, implement data quality checks and alerting, and reduce recurring incidents through runbooks and operational standards.
- Implement data governance and privacy controls: apply masking/access patterns (row-level and column-level controls), support auditability, and ensure safe use of sensitive data across teams.
- Drive cost efficiency through query and pipeline optimization, reducing inefficient scans and improving refresh speed.
- Work closely with stakeholders to translate business requirements into clear data contracts and reusable pipelines, and document datasets/runbooks to reduce knowledge dependency.
What We Need:
- 3+ years of experience as a Data Engineer (or equivalent role) building and operating data pipelines in production.
- Strong SQL skills and solid analytical data modeling fundamentals (curated datasets, performance-aware design, metric standardization).
- Proficiency in Python for pipeline development, automation, and tooling; enjoy building and delivering tools from scratch (reusable modules, validators, utilities).
- Experience working with multiple data sources and formats, including structured and semi-structured/event data.
- Strong debugging and operations mindset: comfortable troubleshooting pipeline failures, handling incidents, and improving system reliability.
- Strong communication and stakeholder management skills; able to drive clarity from ambiguous requirements.
- Experience writing clear and concise documentation (data contracts, dataset definitions, runbooks).